In manufacturing control of products, data are collected for each manufacturing process, and the collected data are aggregated by a human operator to create history data required for manufacturing control. This takes time to create history data, and may cause misaggregation due to human errors. Thus, a technique has been proposed for compiling all the process transition records for all products into a database to create history data based on the process transition records compiled in the database.
However, in such a technique, the database becomes enormous. Furthermore, all the processes are sequentially traced based on the process transition records. This requires more queries than the number of processes, and increases the load on the manufacturing control system. Furthermore, even if the data necessary for creating history data are data of a subset of the processes, all the processes need to be traced. This results in a low efficiency.
Thus, there is demand for a technique capable of performing high-efficiency and appropriate manufacturing control.